最近考虑到这样一个需求：

需要把原始的日志文件用hadoop做清洗后，按业务线输出到不同的目录下去，以供不同的部门业务线使用。

这个需求需要用到MultipleOutputFormat和MultipleOutputs来实现自定义多目录、文件的输出。

需要注意的是，在hadoop 0.21.x之前和之后的使用方式是不一样的：

hadoop 0.21 之前的API 中有 org.apache.hadoop.mapred.lib.MultipleOutputFormat 和 org.apache.hadoop.mapred.lib.MultipleOutputs，而到了 0.21 之后 的API为 org.apache.hadoop.mapreduce.lib.output.MultipleOutputs ，

新版的API 整合了上面旧API两个的功能，没有了MultipleOutputFormat。

本文将给出新旧两个版本的API code。

1、旧版0.21.x之前的版本：

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.conf.Configured;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.io.LongWritable;
import org.apache.hadoop.io.NullWritable;
import org.apache.hadoop.io.Text;
import org.apache.hadoop.mapred.FileInputFormat;
import org.apache.hadoop.mapred.FileOutputFormat;
import org.apache.hadoop.mapred.JobClient;
import org.apache.hadoop.mapred.JobConf;
import org.apache.hadoop.mapred.MapReduceBase;
import org.apache.hadoop.mapred.Mapper;
import org.apache.hadoop.mapred.OutputCollector;
import org.apache.hadoop.mapred.Reporter;
import org.apache.hadoop.mapred.TextInputFormat;
import org.apache.hadoop.mapred.lib.MultipleTextOutputFormat;
import org.apache.hadoop.util.Tool;
import org.apache.hadoop.util.ToolRunner;

public class MultiFile extends Configured implements Tool {

	public static class MapClass extends MapReduceBase implements
			Mapper<LongWritable, Text, NullWritable, Text> {

		@Override
		public void map(LongWritable key, Text value,
				OutputCollector<NullWritable, Text> output, Reporter reporter)
				throws IOException {
			output.collect(NullWritable.get(), value);
		}

	}

	// MultipleTextOutputFormat 继承自MultipleOutputFormat，实现输出文件的分类

	public static class PartitionByCountryMTOF extends
			MultipleTextOutputFormat<NullWritable, Text> { // key is
															// NullWritable,
															// value is Text
		protected String generateFileNameForKeyValue(NullWritable key,
				Text value, String filename) {
			String[] arr = value.toString().split(",", -1);
			String country = arr[4].substring(1, 3); // 获取country的名称
			return country + "/" + filename;
		}
	}

	// 此处不使用reducer
	/*
	 * public static class Reducer extends MapReduceBase implements
	 * org.apache.hadoop.mapred.Reducer<LongWritable, Text, NullWritable, Text>
	 * {
	 * 
	 * @Override public void reduce(LongWritable key, Iterator<Text> values,
	 * OutputCollector<NullWritable, Text> output, Reporter reporter) throws
	 * IOException { // TODO Auto-generated method stub
	 * 
	 * }
	 * 
	 * }
	 */
	@Override
	public int run(String[] args) throws Exception {
		Configuration conf = getConf();
		JobConf job = new JobConf(conf, MultiFile.class);

		Path in = new Path(args[0]);
		Path out = new Path(args[1]);

		FileInputFormat.setInputPaths(job, in);
		FileOutputFormat.setOutputPath(job, out);

		job.setJobName("MultiFile");
		job.setMapperClass(MapClass.class);
		job.setInputFormat(TextInputFormat.class);
		job.setOutputFormat(PartitionByCountryMTOF.class);
		job.setOutputKeyClass(NullWritable.class);
		job.setOutputValueClass(Text.class);

		job.setNumReduceTasks(0);
		JobClient.runJob(job);
		return 0;
	}

	public static void main(String[] args) throws Exception {
		int res = ToolRunner.run(new Configuration(), new MultiFile(), args);
		System.exit(res);
	}

}

hadoop fs -cat /tmp/multiTest.txt
5765303,1998,14046,1996,"AD","",,1,12,42,5,59,11,1,0.4545,0,0,1,67.3636,,,,
5785566,1998,14088,1996,"AD","",,1,9,441,6,69,3,0,1,,0.6667,,4.3333,,,,
5894770,1999,14354,1997,"AD","",,1,,82,5,51,4,0,1,,0.625,,7.5,,,,
5765303,1998,14046,1996,"CN","",,1,12,42,5,59,11,1,0.4545,0,0,1,67.3636,,,,
5785566,1998,14088,1996,"CN","",,1,9,441,6,69,3,0,1,,0.6667,,4.3333,,,,
5894770,1999,14354,1997,"CN","",,1,,82,5,51,4,0,1,,0.625,,7.5,,,,

from：

MultipleOutputFormat Example

2、新版0.21.x及之后的版本：

public class TestwithMultipleOutputs extends Configured implements Tool {

　　public static class MapClass extends Mapper<LongWritable,Text,Text,IntWritable> {

　　　　private MultipleOutputs<Text,IntWritable> mos;

　　　　protected void setup(Context context) throws IOException,InterruptedException {
　　　　　　mos = new MultipleOutputs<Text,IntWritable>(context);
　　　　}

　　　　public void map(LongWritable key, Text value, Context context) throws IOException, InterruptedException{
　　　　　　String line = value.toString();
　　　　　　String[] tokens = line.split("-");

　　　　　　mos.write("MOSInt",new Text(tokens[0]), new IntWritable(Integer.parseInt(tokens[1])));  //（第一处）
　　　　　　mos.write("MOSText", new Text(tokens[0]),tokens[2]);　　　　 //（第二处）
　　　　　　mos.write("MOSText", new Text(tokens[0]),line,tokens[0]+"/");　　//（第三处）同时也可写到指定的文件或文件夹中
　　　　}

　　　　protected void cleanup(Context context) throws IOException,InterruptedException {
　　　　　　mos.close();
　　　　}

　　}
　　public int run(String[] args) throws Exception {

　　　　Configuration conf = getConf();

　　　　Job job = new Job(conf,"word count with MultipleOutputs");

　　　　job.setJarByClass(TestwithMultipleOutputs.class);

　　　　Path in = new Path(args[0]);
　　　　Path out = new Path(args[1]);

　　　　FileInputFormat.setInputPaths(job, in);
　　　　FileOutputFormat.setOutputPath(job, out);

　　　　job.setMapperClass(MapClass.class);
　　　　job.setNumReduceTasks(0);　　

　　　　MultipleOutputs.addNamedOutput(job,"MOSInt",TextOutputFormat.class,Text.class,IntWritable.class);
　　　　MultipleOutputs.addNamedOutput(job,"MOSText",TextOutputFormat.class,Text.class,Text.class);

　　　　System.exit(job.waitForCompletion(true)?0:1);
　　　　return 0;
　　}

　　public static void main(String[] args) throws Exception {

　　　　int res = ToolRunner.run(new Configuration(), new TestwithMultipleOutputs(), args);
　　　　System.exit(res); 
　　}

}

测试的数据：

abc-1232-hdf
abc-123-rtd
ioj-234-grjth
ntg-653-sdgfvd
kju-876-btyun
bhm-530-bhyt
hfter-45642-bhgf
bgrfg-8956-fmgh
jnhdf-8734-adfbgf
ntg-68763-nfhsdf
ntg-98634-dehuy
hfter-84567-drhuk

结果截图：（结果输出到/test/testMOSout）

PS：遇到的一个问题：

　　如果没有mos.close(), 程序运行中会出现异常：

　　12/05/21 20:12:47 WARN hdfs.DFSClient: DataStreamer Exception:

　　org.apache.hadoop.ipc.RemoteException:org.apache.hadoop.hdfs.server.namenode.LeaseExpiredException: No lease on
　　/test/mosreduce/_temporary/_attempt_local_0001_r_000000_0/h-r-00000 File does not exist. [Lease. Holder: DFSClient_-352105532, pendingcreates: 5]

from：

MultipleOutputFormat和MultipleOutputs

http://www.cnblogs.com/liangzh/archive/2012/05/22/2512264.html    

Hadoop利用Partitioner对输出文件分类（改写partition，路由到指定的文件中）

http://superlxw1234.iteye.com/blog/1495465

http://ghost-face.iteye.com/blog/1869926

更多参考&推荐阅读：

1、【Hadoop】利用MultipleOutputs,MultiOutputFormat实现以不同格式输出到多个文件

http://www.cnblogs.com/iDonal/archive/2012/08/07/2626588.html

2、cdh3u3 hadoop 0.20.2 MultipleOutputs 多输出文件初探

http://my.oschina.net/wangjiankui/blog/49521

3、使用MultipleOutputs

http://blog.163.com/ecy_fu/blog/static/444512620101274344951/

4、Hadoop reduce多个输出

http://blog.csdn.net/inte_sleeper/article/details/7042020

5、Hadoop 0.20.2中怎么使用MultipleOutputFormat实现多文件输出和完全自定义文件名

http://www.cnblogs.com/flying5/archive/2011/05/04/2078407.html

6、Hadoop OutputFormat浅析

http://zhb-mccoy.iteye.com/blog/1591635

7、others：

https://sites.google.com/site/hadoopandhive/home/how-to-write-output-to-multiple-named-files-in-hadoop-using-multipletextoutputformat
https://issues.apache.org/jira/browse/HADOOP-3149
http://grokbase.com/t/hadoop/common-user/112ewx7s15/could-i-write-outputs-in-multiple-directories

8、MultipleOutputs 官方范例

http://hadoop.apache.org/docs/stable/api/org/apache/hadoop/mapreduce/lib/output/MultipleOutputs.html

9、多数据源输入：MultipleInputs

http://stackoverflow.com/questions/17456369/mapreduce-job-with-mixed-data-sources-hbase-table-and-hdfs-files

https://groups.google.com/forum/#!topic/nosql-databases/SH61smOV-mo

http://bigdataprocessing.wordpress.com/2012/07/27/hadoop-hbase-mapreduce-examples/

http://hbase.apache.org/book/mapreduce.example.html

10、Hadoop多文件输出：MultipleOutputFormat和MultipleOutputs深究

http://www.iteblog.com/archives/842  （一）

http://www.iteblog.com/archives/848  （二）